Geology topics

Matthew Schauer

Publications and source records attributed to Matthew Schauer.

8 recordsLinked to original sources

USGS2023

Improving the operational simplified surface energy balance evapotranspiration model using the forcing and normalizing operation

Actual evapotranspiration modeling is providing useful information for researchers and resource managers in agriculture and water resources around the world. The performance of models depends on the accuracy of forcing inputs and model parameters. We developed an improved approach to the parameterization of the Operational Simplified Surface Energy Balance (SSEBop) model using the Forcing and Normalizing Operation (FANO). SSEBop has two key model parameters that define the model boundary conditions. The FANO algorithm computes the wet-bulb boundary condition using a linear FANO Equation relating surface temperature, surface psychrometric constant, and the Normalized Difference Vegetation Index (NDVI). The FANO parameterization was implemented on two computing platforms using Landsat and gridded meteorological datasets: (1) Google Earth Engine (GEE) and (2) Earth Resources Observation and Science (EROS) Center Science Processing Architecture (ESPA). Evaluation was conducted by comparing modeled actual evapotranspiration ( ETa ) estimates with AmeriFlux eddy covariance (EC) and water balance ETa from level-8 Hydrologic Unit Code sub-basins in the conterminous United States. FANO brought substantial improvements in model accuracy and operational implementation. Compared to the earlier version (v0.1.7), SSEBop FANO (v0.2.6) reduced grassland bias from 47% to −2% while maintaining comparable bias for croplands (11% versus −7%) against EC data. A water balance-based ETa bias evaluation showed an overall improvement from 7% to −1%. Climatology versus annual gridded reference evapotranspiration ( ETr ) produced comparable ETa results, justifying the use of climatology ETr for the global SSEBop Landsat ETa that is accessible through the ESPA website. Besides improvements in model accuracy, SSEBop FANO increases the spatiotemporal coverage of ET modeling due to the elimination of high NDVI requirements for model parameterization. Because of the existence of potential biases from forcing inputs and model parameters, continued evaluation and bias corrections are necessary to improve the absolute magnitude of ETa for localized water budget applications.

Remote Sensing↗

USGS2022

Mapping actual evapotranspiration using Landsat for the conterminous United States: Google Earth Engine implementation and assessment of the SSEBop model

The estimation and mapping of actual evapotranspiration (ETa) is an active area of applied research in the fields of agriculture and water resources. Thermal remote sensing-based methods, using coarse resolution satellites, have been successful at estimating ETa over the conterminous United States (CONUS) and other regions of the world. In this study, we present CONUS-wide ETa from Landsat thermal imagery-using the Operational Simplified Surface Energy Balance (SSEBop) model in the Google Earth Engine (GEE) cloud computing platform. Over 150,000 Landsat satellite images were used to produce 10 years of annual ETa (2010–2019) at unprecedented scale. The accuracy assessment of the SSEBop results included point-based evaluation using monthly Eddy Covariance (EC) data from 25 AmeriFlux stations as well as basin-scale comparison with annual Water Balance ETa (WBET) for more than 1000 sub-basins. Evaluations using EC data showed generally mixed performance with weaker (R 2 < 0.6) correlation on sparsely vegetated surfaces such as grasslands or woody savanna and stronger correlation (R 2 > 0.7) over well-vegetated surfaces such as croplands and forests, but location-specific conditions rather than cover type were attributed to the variability in accuracy. Croplands performed best with R 2 of 0.82, root mean square error of 29 mm/month, and average bias of 12%. The WBET evaluation indicated that the SSEBop model is strong in explaining the spatial variability (up to R 2 > 0.90) of ETa across large basins, but it also identified broad hydro-climatic regions where the SSEBop ETa showed directional biases, requiring region-specific model parameter improvement and/or bias correction with an overall 7% bias nationwide. Annual ETa anomalies over the 10-year period captured widely reported drought-affected regions, for the most part, in different parts of the CONUS, indicating their potential applications for mapping regional- and field-scale drought and fire effects. Due to the coverage of the Landsat Path/Row system, the availability of cloud-free image pixels ranged from less than 12 (mountainous cloud-prone regions and U.S. Northeast) to more than 60 (U.S. Southwest) per year. However, this study reinforces a promising application of Landsat satellite data with cloud-computing for quick and efficient mapping of ETa for agricultural and water resources assessments at the field scale.

Remote Sensing of Environment↗

USGS2021

Characterization of water use and water balance for the croplands of Kansas using satellite, climate, and irrigation data

Kansas is one of the most productive agricultural states in the United States, where agricultural irrigation is a primary user of underground and surface water. Because of low precipitation and declining groundwater levels in western and central Kansas, sustainable management of irrigation water resources is a critical issue in the agricultural productivity of the state. The objective of this study is to analyze and characterize the water use and water balance in the croplands of Kansas using satellite observations, meteorological data, and in situ irrigation water use records. We used actual evapotranspiration ( ETa ), precipitation, soil moisture, and irrigation water use to calculate water balance for Kansas in 2015 at scales of counties, climatic divisions, and groundwater management districts (GMD). The Operational Simplified Surface Energy Balance model was implemented to estimate 30-m resolution ETa . Results showed that the seasonal (May – September) precipitation, soil water storage change, and ETa are 528 mm, 80 mm, and 555 mm, respectively, on average of all croplands in the state. The annual net irrigation water consumption was 293 mm for irrigated croplands, indicating that irrigation water constitutes an substantial portion of the water supply in the state. The total volumetric irrigation water use was 3.24 km 3 for all croplands within five GMDs in western and south-central Kansas, while only 0.38 km 3 was outside of GMDs. The multiple regression models of ETa against precipitation and irrigation water use were statistically significant with R 2 values of 0.71 and 0.87, respectively, at county and climate division scales. Regression models also indicated a higher rate of ETa response to irrigation water use than that to precipitation. Our study demonstrated the spatial patterns of crop water use and water balance in Kansas, which could provide useful information for management of irrigation agriculture and water resources for the state.

Kansas↗

USGS2020

A novel approach for next generation water use mapping using Landsat and Sentinel-2 satellite data

Evapotranspiration (ET) is needed in a range of applications in hydrology, climatology, ecology, and agriculture. Remote sensing-based estimation is the only viable and economical method for ET estimation over large areas. The current Landsat satellites provide images every 16 days limiting the ability to capture biophysical changes affecting ET. Thus, we explored the potential integration of Landsat 8 and Sentinel-2 data for estimating ET using a surface energy balance model. The results indicate the proposed Landsat-Sentinel data fusion approach substantially reduced relative errors from 48% to 10% on area-wide and from 49% to 17% on pixel-wide compared to linear interpolation between two Landsat images. The proposed approach had a better agreement with expected actual ET maps across high-vegetation conditions than in low-vegetation conditions. The finer temporal resolution and better accuracy of ET maps based on Landsat-Sentinel integration is of great importance in managing limited water resources.

Arizona, California↗

USGS2020

Evaluation of hydrologic impact of an irrigation curtailment program in the Upper Klamath Lake Basin using Landsat satellite data

Upper Klamath Lake (UKL) is the source of the Klamath river that flows through southern Oregon and northern California. The UKL basin is home to two endangered species and provides water for 81,000+ ha (200,000+ acres) of irrigation on the United States Bureau of Reclamation (USBR) Klamath Project located downstream of the UKL basin. Irrigated agriculture also occurs along the tributaries to UKL. During 2013–2016, water right calls resulted in various levels of curtailment of irrigation diversions from the tributaries to UKL. However, information on the extent of curtailment, how much irrigation water was saved, and its impact on the UKL is unknown. In this study, we combined Landsat-based actual evapotranspiration (ETa) data obtained from the Operational Simplified Surface Energy Balance (SSEBop) model with gridded precipitation and USGS station discharge data to evaluate the hydrologic impact of the curtailment program. Analysis was performed for five base years (2004, 2006, 2008-2010) and four target years (2013-2016) over irrigated areas above UKL. Our results indicated that the impact of the curtailment program over the June to September time-period was highest during 2013 and declined in each of the following years. The total on-field water savings were approximately 60 hm3 in 2013 and 2014, 44 hm3 in 2015, and 32 hm3 in 2016. The instream water flow change or extra water available (EWA) were found at 92, 68, 45, and 26 hm3 respectively for 2013, 2014, 2015 and 2016. Most water savings came from pasture and wetlands. Alfalfa showed the most decline in water use among grain crops. The resulting EWA from the curtailment contributed to a maximum of 19% of the lake inflows and 50% of the lake volume. This study presents the use of Landsat-based ETa and other remote sensing datasets for evaluating water-related impacts of the irrigation curtailment program.

Upper Klamath Lake Basin↗

USGS2019

Characterizing crop water use dynamics in the Central Valley of California using landsat-derived evapotranspiration

Understanding how different crops use water over time is essential for planning and managing water allocation, water rights, and agricultural production. The main objective of this paper is to characterize the spatiotemporal dynamics of crop water use in the Central Valley of California using Landsat-based annual actual evapotranspiration (ETa) from 2008 to 2018 derived from the Operational Simplified Surface Energy Balance (SSEBop) model. Crop water use for 10 crops is characterized at multiple scales. The Mann–Kendall trend analysis revealed a significant increase in area cultivated with almonds and their water use, with an annual rate of change of 16,327 ha in area and 13,488 ha-m in water use. Conversely, alfalfa showed a significant decline with 12,429 ha in area and 13,901 ha-m in water use per year during the same period. A pixel-based Mann–Kendall trend analysis showed the changing crop type and water use at the level of individual fields for all of Kern County in the Central Valley. This study demonstrates the useful application of historical Landsat ET to produce relevant water management information. Similar studies can be conducted at regional and global scales to understand and quantify the relationships between land cover change and its impact on water use.

California↗

USGS2019

Long-term (1986–2015) crop water use characterization over the Upper Rio Grande Basin of United States and Mexico using Landsat-based evapotranspiration

The evaluation of historical water use in the Upper Rio Grande Basin (URGB), United States and Mexico, using Landsat-derived actual evapotranspiration (ETa) from 1986 to 2015 is presented here as the first study of its kind to apply satellite observations to quantify long-term, basin-wide crop consumptive use in a large basin. The rich archive of Landsat imagery combined with the Operational Simplified Surface Energy Balance (SSEBop) model was used to estimate and map ETa across the basin and over irrigated fields for historical characterization of water-use dynamics. Monthly ETa estimates were evaluated using six eddy-covariance (EC) flux towers showing strong correspondence (r2 > 0.80) with reasonable error rates (root mean square error between 6 and 19 mm/month). Detailed spatiotemporal analysis using peak growing season (June–August) ETa over irrigated areas revealed declining regional crop water-use patterns throughout the basin, a trend reinforced through comparisons with gridded ETa from the Max Planck Institute (MPI). The interrelationships among seven agro-hydroclimatic variables (ETa, Normalized Difference Vegetation Index (NDVI), land surface temperature (LST), maximum air temperature (Ta), potential ET (ETo), precipitation, and runoff) are all summarized to support the assessment and context of historical water-use dynamics over 30 years in the URGB.

Colorado, New Mexico, Texas↗

USGS2017

Satellite-based water use dynamics using historical Landsat data (1984–2014) in the southwestern United States

Remote sensing-based field-scale evapotranspiration (ET) maps are useful for characterizing water use patterns and assessing crop performance. The relative impact of climate variability and water management decisions are better studied and quantified using historical data that are derived using a set of consistent datasets and methodology. Historical (1984–2014) Landsat-based ET maps were generated for major irrigation districts in California, i.e., Palo Verde and eight other sub-basins in parts of the middle and lower Central Valley. A total of 3396 Landsat images were processed using the Operational Simplified Surface Energy Balance (SSEBop) model that integrates weather and remotely sensed images to estimate monthly and annual ET within the study sites over the 31 years. Model output evaluation and validation using gridded-flux data and water balance ET approaches indicated relatively good correspondence (R 2 up to 0.88, root mean square error as low as 14 mm/month) between SSEBop ET and validation datasets. In a pairwise comparison, annual variability of agro-hydrologic parameters of actual evapotranspiration ( ET a ), land surface temperature ( T s ), and runoff ( Q ) were found to be more variable than their corresponding climatic counterparts of atmospheric water demand ( ET o ), air temperature ( T a ), and precipitation ( P ), revealing process differences between regional climatic drivers and localized agro-hydrologic responses. However, only T a showed a consistent increase (up to 1.2 K) over study sites during the 31 years, whereas other climate variables such as ET o and P showed a generally neutral trend. This study demonstrates a useful application of “Big Data” science where large volumes of historical Landsat and weather datasets were used to quantify and understand the relative importance of water management and climate variability in crop water use dynamics in regards to the linkages among water management decisions, hydrologic processes and economic transactions. Irrigation district-wide ET a estimates were used to compute historical crop water use volumes and monetary equivalents of water savings for the Palo Verde Irrigation District (PVID). During the peak crop fallowing year in PVID, the water saved reached a maximum of ~ 107,200 acre-feet in 2011 with an estimated monetary payout value of $20.5 million. A significant decreasing trend in actual ET despite an increasing atmospheric demand in PVID highlights the role of management decisions in affecting local hydrologic processes. This study has importance for planning water resource allocation, managing water rights, sustaining agricultural production, and quantifying impacts of climate and land use/land cover changes on water resources. With increased computational efficiency, similar studies can be conducted in other parts of the world to help policy and decision makers understand and quantify various aspects of water resources management.

Arizona, California↗